2 citations · 2 across the 4 of their papers we have counts for
5 papers
Mind What Matters for Reasoning: Aligning Cross-Modal Attention via Selective Probability Mass Concentration
Jiaqi Deng, Zonghan Wu, Zhan Heng +3
Multimodal large language models (MLLMs) achieve strong performance on visual reasoning tasks, yet remain prone to hallucinations and over-reliance on language priors, often genera…
Quality-Aware Collaborative Multi-Positive Contrastive Learning for Sequential Recommendation
Wei Wang, Yujie Lin, Moyan Zhang +5
The effectiveness of contrastive learning in sequential recommendation hinges on the construction of contrastive views, which ideally should be both semantically consistent and div…
Cloud-Device Collaborative Agents for Sequential Recommendation
Jing Long, Sirui Huang, Huan Huo +3
Recent advances in large language models (LLMs) have enabled agent-based recommendation systems with strong semantic understanding and flexible reasoning capabilities. While LLM-ba…
A Comprehensive Survey of Knowledge-Based Vision Question Answering Systems: The Lifecycle of Knowledge in Visual Reasoning Task
Jiaqi Deng, Zonghan Wu, Huan Huo +1
Knowledge-based Vision Question Answering (KB-VQA) extends general Vision Question Answering (VQA) by not only requiring the understanding of visual and textual inputs but also ext…
Enabling Collaborative Parametric Knowledge Calibration for Retrieval-Augmented Vision Question Answering
Jiaqi Deng, Kaize Shi, Zonghan Wu +3
Knowledge-based Vision Question Answering (KB-VQA) systems address complex visual-grounded questions with knowledge retrieved from external knowledge bases. The tasks of knowledge…